Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import gradio as gr
 import os
 import torch
@@ -11,7 +12,8 @@ from transformers import (
 from scipy.io.wavfile import write
 import tempfile
 from dotenv import load_dotenv
-import spaces  
+import spaces
+
 
 load_dotenv()
 hf_token = os.getenv("HF_TOKEN")
@@ -20,7 +22,7 @@ hf_token = os.getenv("HF_TOKEN")
 # ---------------------------------------------------------------------
 # Load Llama 3 Pipeline with Zero GPU (Encapsulated)
 # ---------------------------------------------------------------------
-@spaces.GPU(duration=300)  
+@spaces.GPU(duration=300)  # GPU allocation for 300 seconds
 def generate_script(user_prompt: str, model_id: str, token: str):
     try:
         tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=token)
@@ -34,9 +36,9 @@ def generate_script(user_prompt: str, model_id: str, token: str):
         llama_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
         system_prompt = (
-    "You are an expert radio imaging producer specializing in sound design and music. "
-    "Take the user's concept and craft a concise, creative promo script with a strong focus on auditory elements and musical appeal."
-)
+            "You are an expert radio imaging producer specializing in sound design and music. "
+            "Take the user's concept and craft a concise, creative promo script with a strong focus on auditory elements and musical appeal."
+        )
 
         combined_prompt = f"{system_prompt}\nUser concept: {user_prompt}\nRefined script:"
         result = llama_pipeline(combined_prompt, max_new_tokens=200, do_sample=True, temperature=0.9)
@@ -71,7 +73,7 @@ def generate_audio(prompt: str, audio_length: int):
 
 
 # ---------------------------------------------------------------------
-# Gradio Interface
+# Gradio Interface Functions
 # ---------------------------------------------------------------------
 def interface_generate_script(user_prompt, llama_model_id):
     return generate_script(user_prompt, llama_model_id, hf_token)
@@ -115,23 +117,22 @@ with gr.Blocks() as demo:
     )
 
     # Audio Generation Section
-gr.Markdown("## 🎧 Step 2: Generate Audio from Your Script")
-with gr.Row():
-    audio_length = gr.Slider(
-        label="🎵 Audio Length (tokens)",
-        minimum=128,
-        maximum=1024,
-        step=64,
-        value=512,
-        info="Select the desired audio token length."  # `info` is valid here
+    gr.Markdown("## 🎧 Step 2: Generate Audio from Your Script")
+    with gr.Row():
+        audio_length = gr.Slider(
+            label="🎵 Audio Length (tokens)",
+            minimum=128,
+            maximum=1024,
+            step=64,
+            value=512,
+            info="Select the desired audio token length."  
+        )
+    generate_audio_button = gr.Button("Generate Audio 🎶")
+    audio_output = gr.Audio(
+        label="🎶 Generated Audio File",
+        type="filepath",
+        interactive=False
     )
-generate_audio_button = gr.Button("Generate Audio 🎶")
-audio_output = gr.Audio(
-    label="🎶 Generated Audio File",
-    type="filepath",  # Removed the `info` argument
-    interactive=False
-)
-
 
     # Footer
     gr.Markdown("""